**Link**: Machine learning

## What is bias variance trade off

## Beginner’s error: overfit model

- Beginner’s error: make model more complicated and “overfit”
- As a result, the model is overfit and performs poorly when forecasting with the test dataset

## How to evaluate?

Plot the complicity/flexibility of the model, by **the polynomial level of a regression fit** vs **error metrics** (Mean Squared Error MSE).

### Find the balanced point

Find the point that’s good enough to balance out the bias and the variance